Question 1

Your team has built a new robot that roams the halls at your organization and helps with various things such as small deliveries. However, you notice that many employees are opting not to use the robot. When you ask them why they tell you that the robot looks "creepy" and they would rather not interact with it. What's going on here?

Options :

A : Lack of understanding the robot's usefulness

B : The bot is falling into The "Uncanny Valley"

C : Bias towards the robot

D : Safety and reliability issues that impact bot usefulness

Answer: B

Question 2

You are working with a dataset that has a high number of dimensions. You're running into issues because some dimensions don't have enough real examples to properly train the systems for predictable results. What's your best course of action?

Options :

A : Keep going as planned and the problem will eventually correct itself

B : Try to get additional data - at least 5 training examples for each dimension in the representation

C : Try to get additional information from project lead to see how many examples per dimension are needed

D : Try to improve the quality of your data through more preparation

Answer: B

Question 3

You're working on a project and are working with personally identifiable information (PII). What's the best approach to take when it comes to collecting and using this data?

Options :

A : Use noise reduction techniques to reduce all forms of data noise

B : Implement a new data privacy policy

C : Store the data in a data warehouse

D : If this data is not needed, use Data anonymization techniques to remove it before feeding to models

Answer: D

Question 4

Your team is running a simulation-based optimization exercise to increase routing efficiency. Learning for this exercise is done through "trial and error". Which type of machine learning approach is being leveraged for this exercise?

Options :

A : Unsupervised Learning

B : Reinforcement Learning

C : Supervised Learning

D : All would work equally well

Answer: B

Question 5

A project manager meets with a customer for initial discussions about an upcoming project. At the end of the meeting, the customer asks the project manager for a rough estimate of the project duration. Based on her experience with three similar projects, the project manager provides an estimate of 8-10 months. What's wrong with this timeframe?

Options :

A : It's underestimating the project timeline by 3 months

B : It fits into a waterfall timeframe, but not an agile project timeframe

C : It's not accounting for data preparation timelines

D : It's not accounting for potential project delays

Answer: D

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